guidance Skill
Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework Published by NousResearch in hermes-agent.
What is guidance Skill?
Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework Published by NousResearch in hermes-agent. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Research
- Research use cases
Technical details
- Install or run with Copy skill directory
When to use guidance Skill
- Use it for research.
Built with
Editorial notes
Source
- Creator: NousResearch
- Repository: NousResearch/hermes-agent
- Skill file: optional-skills/mlops/guidance/SKILL.md
What it does
Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation framework
Skill instructions
Guidance: Constrained LLM Generation When to Use This Skill Use Guidance when you need to: - Control LLM output syntax with regex or grammars - Guarantee valid JSON/XML/code generation - Reduce latency vs traditional prompting approaches - Enforce structured formats (dates, emails, IDs, etc.) - Build multi-step workflows with Pythonic control flow - Prevent invalid outputs through grammatical constraints GitHub Stars: 18,000+ | From: Microsoft Research Installation bash Base installation pip install guidance With specific backends pip install guidance[transformers] Hugging Face models pip install guidance[llamacpp] llama.cpp models Quick Start Basic Example: Structured Generation python from guidance import models, gen Load model (supports OpenAI, Transformers, llama.cpp) lm = models.OpenAI("gpt-4") Generate with constraints result = lm + "The capital of France is " + gen("capital", maxtokens=5) print(result["capital"]) "Paris" With Anthropic Claude python from guidance import models,
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Frequently asked questions
What is guidance?
guidance is a open-source AI agent skill with Copy skill directory. Control LLM output with regex and grammars, guarantee valid JSON/XML/code generation, enforce structured formats, and build multi-step workflows with Guidance - Microsoft Research's constrained generation.
Who is guidance best for?
guidance is best for reusing agent instructions, scripts, and references, research workflows.
How do I install guidance?
Install or run guidance using Copy skill directory. Check guidance for the latest setup command.
Is guidance actively maintained?
guidance may need a closer maintenance check before production use.
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